Statistics for Policy Analysis II

This course examines econometric methods for identifying and estimating causal relationships in public policy analysis. Students study the Rubin causal framework, randomized controlled trials, and a range of quasi‑experimental designs including natural experiments, instrumental variables, regression discontinuity, difference‑in‑differences, and propensity score matching.

Emphasis is placed on both conceptual foundations and applied implementation using statistical software. Through analysis of journal articles and hands‑on exercises, students learn to formulate causal questions, evaluate study designs, and apply appropriate methods. By the end, they are equipped to critically assess and conduct empirical research that informs evidence‑based policy decisions.